Watch the recording, read the webinar slides and discover the Q&A resources below.
Q&A session summary
1. Does tide affect laytime?
Tide can indeed have an impact on laytime, especially on load ports. As we showed, we will provide a warning when it’s a tidal restricted terminal, where it seems your vessel might not be able to do a full load. The actual optimisation is up to the operator.
2. Are swell conditions monitored, particularly where swell periods have changed dramatically in recent years?
We monitor swell delays based on digitalised SOFs. For impacted ports like Tocopilla, there will be a warning and a seasonal impact chart.
3. Would you be able to share how the weather prediction process works, specifically in terms of rain patterns?
We are getting rain patterns from meteorological institutes around the world. But rainfall is not enough to predict rain impact. We combine data with our SOF-based observations to determine patterns on a combination of port/commodity/month.
4. How dependent is PortLog on the feedback of agents and captains?
A key data source we use is SOFs, which we collect from agents. For the majority of ports/agents this works well based on an instruction in the agent nomination letter. Please note that we are not dependent on captains.
5. Can our own insights to be seen within IMOS or is this limited to only Marcura Observations?
You have the option to enter and tag your own insights, which will not be shared with others. Currently these are available from within PortLog only, but this could be discussed for developement.
6. If the user wants to modify the suggestion via alerts, where can they do this?
After doing your simulations/optimisations inside PortLog, you can use the « push back » feature to send the results back to the IMOS calculation.
7. Do you work with Softmar?
Yes we do.
8. What level of accuracy is deemed acceptable for predicting unpaid time allocation in both laytime calculations and chartering costs?
Every month we test our logic against tens of thousands of actual DAs and laytime results, which helps us constantly improve the accuracy.
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